Mostly just add an explicit cast when calling `malloc` and its
variants. Sometimes instead change the type of a local variable if
this would silence multiple warnings.
* re: https://github.com/Unidata/netcdf-c/pull/2278
* re: https://github.com/Unidata/netcdf-c/issues/2485
* re: https://github.com/Unidata/netcdf-c/issues/2474
This PR subsumes PR https://github.com/Unidata/netcdf-c/pull/2278.
Actually is a bit an omnibus covering several issues.
## PR https://github.com/Unidata/netcdf-c/pull/2278
Add support for the Zarr string type.
Zarr strings are restricted currently to be of fixed size.
The primary issue to be addressed is to provide a way for user to
specify the size of the fixed length strings. This is handled by providing
the following new attributes special:
1. **_nczarr_default_maxstrlen** —
This is an attribute of the root group. It specifies the default
maximum string length for string types. If not specified, then
it has the value of 64 characters.
2. **_nczarr_maxstrlen** —
This is a per-variable attribute. It specifies the maximum
string length for the string type associated with the variable.
If not specified, then it is assigned the value of
**_nczarr_default_maxstrlen**.
This PR also requires some hacking to handle the existing netcdf-c NC_CHAR
type, which does not exist in zarr. The goal was to choose numpy types for
both the netcdf-c NC_STRING type and the netcdf-c NC_CHAR type such that
if a pure zarr implementation read them, it would still work and an
NC_CHAR type would be handled by zarr as a string of length 1.
For writing variables and NCZarr attributes, the type mapping is as follows:
* "|S1" for NC_CHAR.
* ">S1" for NC_STRING && MAXSTRLEN==1
* ">Sn" for NC_STRING && MAXSTRLEN==n
Note that it is a bit of a hack to use endianness, but it should be ok since for
string/char, the endianness has no meaning.
For reading attributes with pure zarr (i.e. with no nczarr
atribute types defined), they will always be interpreted as of
type NC_CHAR.
## Issue: https://github.com/Unidata/netcdf-c/issues/2474
This PR partly fixes this issue because it provided more
comprehensive support for Zarr attributes that are JSON valued expressions.
This PR still does not address the problem in that issue where the
_ARRAY_DIMENSION attribute is incorrectly set. Than can only be
fixed by the creator of the datasets.
## Issue: https://github.com/Unidata/netcdf-c/issues/2485
This PR also fixes the scalar failure shown in this issue.
It generally cleans up scalar handling.
It also adds a note to the documentation describing that
NCZarr supports scalars while Zarr does not and also how
scalar interoperability is achieved.
## Misc. Other Changes
1. Convert the nczarr special attributes and keys to be all lower case. So "_NCZARR_ATTR" now used "_nczarr_attr. Support back compatibility for the upper case names.
2. Cleanup my too-clever-by-half handling of scalars in libnczarr.
cloud using a variant of the Zarr protocol and storage
format. This enhancement is generically referred to as "NCZarr".
The data model supported by NCZarr is netcdf-4 minus the user-defined
types and the String type. In this sense it is similar to the CDF-5
data model.
More detailed information about enabling and using NCZarr is
described in the document NUG/nczarr.md and in a
[Unidata Developer's blog entry](https://www.unidata.ucar.edu/blogs/developer/en/entry/overview-of-zarr-support-in).
WARNING: this code has had limited testing, so do use this version
for production work. Also, performance improvements are ongoing.
Note especially the following platform matrix of successful tests:
Platform | Build System | S3 support
------------------------------------
Linux+gcc | Automake | yes
Linux+gcc | CMake | yes
Visual Studio | CMake | no
Additionally, and as a consequence of the addition of NCZarr,
major changes have been made to the Filter API. NOTE: NCZarr
does not yet support filters, but these changes are enablers for
that support in the future. Note that it is possible
(probable?) that there will be some accidental reversions if the
changes here did not correctly mimic the existing filter testing.
In any case, previously filter ids and parameters were of type
unsigned int. In order to support the more general zarr filter
model, this was all converted to char*. The old HDF5-specific,
unsigned int operations are still supported but they are
wrappers around the new, char* based nc_filterx_XXX functions.
This entailed at least the following changes:
1. Added the files libdispatch/dfilterx.c and include/ncfilter.h
2. Some filterx utilities have been moved to libdispatch/daux.c
3. A new entry, "filter_actions" was added to the NCDispatch table
and the version bumped.
4. An overly complex set of structs was created to support funnelling
all of the filterx operations thru a single dispatch
"filter_actions" entry.
5. Move common code to from libhdf5 to libsrc4 so that it is accessible
to nczarr.
Changes directly related to Zarr:
1. Modified CMakeList.txt and configure.ac to support both C and C++
-- this is in support of S3 support via the awd-sdk libraries.
2. Define a size64_t type to support nczarr.
3. More reworking of libdispatch/dinfermodel.c to
support zarr and to regularize the structure of the fragments
section of a URL.
Changes not directly related to Zarr:
1. Make client-side filter registration be conditional, with default off.
2. Hack include/nc4internal.h to make some flags added by Ed be unique:
e.g. NC_CREAT, NC_INDEF, etc.
3. cleanup include/nchttp.h and libdispatch/dhttp.c.
4. Misc. changes to support compiling under Visual Studio including:
* Better testing under windows for dirent.h and opendir and closedir.
5. Misc. changes to the oc2 code to support various libcurl CURLOPT flags
and to centralize error reporting.
6. By default, suppress the vlen tests that have unfixed memory leaks; add option to enable them.
7. Make part of the nc_test/test_byterange.sh test be contingent on remotetest.unidata.ucar.edu being accessible.
Changes Left TO-DO:
1. fix provenance code, it is too HDF5 specific.
re: issue https://github.com/Unidata/netcdf-c/issues/1233
Changes:
1. remove exit that was there for testing.
2. the program tst_open_mem must be netcdf-4 only.
3. fix some diff problems
- Change dataset name for tst_inmemory4_create to tst_inmemory4
- Modify tst_inmemory.c to reorder the variables (somewhat major rewrite)
Minor Unrelated Fixes:
1. fix comment problem in nc_provenance.h
2. Fix memory leak in tst_open_mem.c
3. fix ncdump/bindata.c to properly compile if netcdf4 is disabled.
4. minor changes to ncgen.l
This is a follow up to PR https://github.com/Unidata/netcdf-c/pull/1173
Sorry that it is so big, but leak suppression can be complex.
This PR fixes all remaining memory leaks -- as determined by
-fsanitize=address, and with the exceptions noted below.
Unfortunately. there remains a significant leak that I cannot
solve. It involves vlens, and it is unclear if the leak is
occurring in the netcdf-c library or the HDF5 library.
I have added a check_PROGRAM to the ncdump directory to show the
problem. The program is called tst_vlen_demo.c To exercise it,
build the netcdf library with -fsanitize=address enabled. Then
go into ncdump and do a "make clean check". This should build
tst_vlen_demo without actually executing it. Then do the
command "./tst_vlen_demo" to see the output of the memory
checker. Note the the lost malloc is deep in the HDF5 library
(in H5Tvlen.c).
I am temporarily working around this error in the following way.
1. I modified several test scripts to not execute known vlen tests
that fail as described above.
2. Added an environment variable called NC_VLEN_NOTEST.
If set, then those specific tests are suppressed.
This should mean that the --disable-utilities option to
./configure should not need to be set to get a memory leak clean
build. This should allow for detection of any new leaks.
Note: I used an environment variable rather than a ./configure
option to control the vlen tests. This is because it is
temporary (I hope) and because it is a bit tricky for shell
scripts to access ./configure options.
Finally, as before, this only been tested with netcdf-4 and hdf5 support.
